songpeng update

spark/bootstarp/dependencies.py

@@ -10,6 +10,7 @@ from sources import Sources, Sinks
 
 
 def getColumns(x):
+    try:
         sql_list = []
         sql_file_list = []
         list = [i for i in json.loads(x).get('col')]
@@ -30,6 +31,8 @@ def getColumns(x):
 
         for i in sql_file_list:
             col_file += i + ','
+    except Exception as e:
+        print("index error:{0}".format(e))
 
     sql = "select " + col + " current_timestamp() as create_time from kino"
     sql_file = "select " + col_file[0:-1] + " from kino"

spark/sources/Sinks.py

 from common import Constants
-import exception.MyErrorException as ex
+import os
 
 # 写出到 MySQL
-from sources import Sources
-
-
 def sinkMySql(sinkDF, driver, url, user, password, table, mode=Constants.SAVE_MODE_OVERWRITE):
     sinkDF.write.mode(mode) \
         .format("jdbc") \
@@ -38,6 +35,9 @@ def sinkFTP(sinkDF, host, user, password, filetype, file, delimiter):
 
 # sink HDFS
 def sinkHDFS(sinkDF, path, delimiter, format="parquet", mode=Constants.SAVE_MODE_OVERWRITE):
+    if os.system("hdfs dfs -test -e path") != 0:
+        print("hdfsPath not exists")
+    else:
         sinkDF\
             .write\
             .format(format) \
@@ -49,14 +49,16 @@ def sinkHDFS(sinkDF, path, delimiter, format="parquet", mode=Constants.SAVE_MODE
 # 修改 MySQL 状态
 def updateMysqlStatus(i_status, i_readcount, i_sinkcount, i_id):
     try:
+        #  see = 1 /0
         conn = Sources.getMySqlConnect()
         # 创建游标对象,用来给数据库发送sql语句
         cur = conn.cursor()
         serch_data = """update uptable set status={status}, readcount={readcount}, sinkcount={sinkcount} where id = {id}"""\
             .format(status=i_status, readcount=i_readcount, sinkcount=i_sinkcount, id=i_id)
         result = cur.execute(serch_data)
-    except ex.MyError as e:
-        print("update error", e.errorinfo)
+    except Exception as e:
+        print("update error: {0}".format(e))
     finally:
         cur.close()  # 关闭数据库连接
         conn.close()
+

spark/sources/Sources.py

@@ -15,8 +15,8 @@ def getMySqlConnect():
             charset="utf8",  # 指定编码格式
             autocommit=True,  # 如果插入数据，， 是否自动提交? 和conn.commit()功能一致。
         )
-    except ex.MyError as e:
-        print("connection error", e.errorinfo)
+    except Exception as e:
+        print("connection error:{0}".format(e))
         Sinks.updateMysqlStatus(i_status=1, i_readcount=0, i_sinkcount=0, i_id=1)
     return conn
 
@@ -30,10 +30,9 @@ def getRecordByIdResultT1(id):
         result = cur.execute(serch_data)
         # 获取下一个查询结果集
         record = cur.fetchone()
-    except ex.MyError as e:
+    except Exception as e:
         Sinks.updateMysqlStatus(i_status=1, i_readcount=0, i_sinkcount=0, i_id=1)
-        print("executor failed", e.errorinfo)
-        conn.rollback()
+        print("executor failed:{0}".format(e))
     finally:
         cur.close()  # 关闭数据库连接
         conn.close()
@@ -43,18 +42,18 @@ def getRecordByIdResultT1(id):
 def readCsv(spark, path, col):
     try:
         df = spark.read.format('csv').option('inferSchema', 'true').load(path).toDF(*col)
-    except ex.MyError as e:
+    except Exception as e:
         Sinks.updateMysqlStatus(i_status=1, i_readcount=0, i_sinkcount=0, i_id=1)
-        print("executor failed", e.errorinfo)
+        print("executor failed:{0}".format(e))
     return df
 
 
-def readTxt(spark, path, delimiter, *col):
+def readTxt(spark, path, delimiter, col):
     try:
-        rddFile = SparkContext.textFile(path)
+        rddFile = spark.SparkContext.textFile(path)
         rddMap = rddFile.map(lambda x: x.split(delimiter))
-        df = spark.createDataFrame(rddMap, *col)
-    except ex.MyError as e:
+        df = spark.createDataFrame(rddMap, col)
+    except Exception as e:
         Sinks.updateMysqlStatus(i_status=1, i_readcount=0, i_sinkcount=0, i_id=1)
-        print("executor failed", e.errorinfo)
+        print("executor failed:{0}".format(e))
     return df
\ No newline at end of file

spark/sources/get_message_info.py

@@ -4,8 +4,6 @@ import os
 2.判断数据库状态是否是失败状态
 ①判断目标表是否有数据,如果有就将数据回滚
 ②判断写入的文件是否存在,如果存在直接删除
-传入的id,数据库库名,表名,用户名,密码  后端传入的用户名和密码需加密传入
-我们定义udf函数将拿到的加密字段进行解密
 '''
 def getMessage(file):
     file = os.path.basename(file)

spark/unzip.py

@@ -2,7 +2,6 @@
 import sys
 import os
 import shutil
-import exception.MyErrorException as ex
 import zipfile
 
 
@@ -10,8 +9,6 @@ pyName = sys.argv[0]  # sys.argv[0] 类似于shell中的$0, 但不是脚本名
 zipPath = sys.argv[1]  # sys.argv[1] 表示传入的第一个参数
 inputPath = sys.argv[2]  # sys.argv[2] 表示传入的第二个参数
 outputPath = sys.argv[3]
-#问题:解压的时候要考虑密码吗???
-
 # os.system("hdfs dfs -put /srcPath /dstPath")
 def get_file(srcPath, dstPath):
 
@@ -37,8 +34,8 @@ def unzip_single(srcPath, dstPath):
     zf = zipfile.ZipFile(srcPath)
     try:
         zf.extractall(path=dstPath)
-    except ex.MyError as e:
-        print(e)
+    except FileNotFoundError as e:
+        print("zipPath not exists:{0}".format(e))
     zf.close()